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Artificial Intelligence: Introducing AI

General information and guidance on the use of AI for the UCD community
"You will never be replaced by AI, but you will be replaced by someone who knows how to use AI." (Sonnenberg, 2025)

 


Figure 1. An AI Generated image
An array of circuits depicting the interconnectedness of information and technology, lighter optimistic colour palette
Note. Image generated using Midjourney. The image was generated in response to the prompt: An array of circuits depicting the interconnectedness of information and technology, lighter optimistic colour palette (chaos 25; Stylize 750; weird 1500).

What is Artificial Intelligence? (Anthropic, 2025)

 

Artificial Intelligence (AI) encompasses a range of technologies and methodologies that enable computers to perform tasks typically requiring human intelligence. From machine learning algorithms to natural language processing, AI has become an integral part of academic research, industry applications, and daily life.

As AI continues to evolve and shape various disciplines, understanding its foundations, capabilities, and limitations becomes increasingly important for researchers and students. This guide provides curated resources to help you navigate the complex landscape of AI, including fundamental concepts, current developments, and ethical considerations. Whether you're conducting research, exploring AI tools for academic work, or seeking to understand AI's impact on your field of study, you'll find relevant resources and guidance here.


A Brief Definition

Artificial Intelligence (AI) is defined as the capability of a computer system or algorithm to imitate intelligent human behavior. According to Merriam-Webster, it involves the simulation of human intelligence processes by machines, especially computer systems (Gove et al., 1981). Britannica describes AI as the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings, such as reasoning, learning, and problem-solving (Copeland, 2025).


A Bit of Background (Microsoft, 2025)

The development of AI began in the mid-20th century, with significant milestones marking its evolution. In 1956, the Dartmouth Conference, organized by John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon, is often considered the birth of AI as a field. This conference introduced the term "artificial intelligence" and set the stage for future research. During the 1960s and 1970s, AI research focused on problem-solving and symbolic methods, leading to the creation of early AI programs like ELIZA and SHRDLU.

The 1980s and 1990s saw the rise of machine learning, a subset of AI that enables systems to learn from data. This period also witnessed the development of expert systems, which were designed to mimic the decision-making abilities of human experts. The turn of the 21st century brought significant advancements in AI, driven by increased computational power and the availability of large datasets. Breakthroughs in deep learning, a type of machine learning inspired by the structure of the human brain, have led to remarkable achievements in image and speech recognition, natural language processing, and autonomous systems. Today, AI continues to evolve rapidly, with applications spanning various industries, from healthcare to finance and beyond.

For additional information on the development of AI, see also the Timeline of Artificial Intelligence in "Are You AI Ready?"

References (APA):

Anthropic Claude 3.5 Sonnet  (2025) Claude.ai response to Sandra Dunkin 17 February. 

Copeland, B. (2025, February 17). artificial intelligence. Encyclopedia Britannica. https://www.britannica.com/technology/artificial-intelligence.

Coursera.org, (2024, October 25) "The History of AI: A Timeline of Artificial Intelligence". AI and Machine Learning. Retrieved 17 February 2025 from: https://www.coursera.org/articles/history-of-ai.

Gove, P. B., G, & Company, C. M. (1981). Webster's third new international dictionary of the English language, unabridged. G. & C. Merriam Co. https://go.exlibris.link/NKRVSVsN

Microsoft Copilot (2025) Copilot response to Sandra Dunkin 17 February. 

Midjourney Inc. (2025) Midjourney (6.1) [AI image generator]. https://www.midjourney.com

Sonnenbeg, Dr. Lyn (Speaker). (2025, April 10), Responsible AI Use: Applying the CARE-AI Framework to Real-World Scenarios [Webinar]. Contact North/Contact Nord. https://teachonline.ca/webinar/responsible-ai-use-applying-care-ai-framework-real-world-scenarios

Spoeth, A. (2025). AI Timeline: A Journey Through the History of Artificial Intelligence. The AI Navigator. Retrieved 17 February from https://www.theainavigator.com/ai-timeline

 

AI in Higher Education

Midjourney generated image from the prompt: "A photograph of a sunny afternoon, a group of students stand chatting outside the library. The students are a diverse selection of ethnicities, one individual is in a wheelchair.
Midjourney generated image of a photograph of a sunny afternoon, a group of students stand chatting outside the library. The students are a diverse selection of ethnicities, one individual is in a wheelchair1

 

AI is being discussed in the university sector because it has the potential to impact a number of university activities including:

  • Teaching and learning practice
  • Academic integrity
  • Assessment
  • Academic publishing
  • Intellectual property - Copyright
  • Administration - Automation of work tasks

Generative AI is drawing attention in higher education because tools like ChatGPT can pass engineering exams, impact essay mills and create deep fake images, audio and video, essentially manipulating reality.

Recently AI has been reported as an issue in Library practice because it can generate search strategies and fake citations, which creates interlibrary loan and other queries for non-existent items.

UCD is responding to facets of AI through working groups such as the University Working Group on Development, Governance and Management of Use of AI. However, while AI and related tools are evolving rapidly, creating policy in this area is a complex and extended process and it will take time to get it right.

References (Vancouver):
1. Midjourney v.6.1. Response to "A photograph of a sunny afternoon, a group of students stand chatting outside the library. The students are a diverse selection of ethnicities, one individual is in a wheelchair." AI Generated image. Midjourney Inc. 25 February 2025

 

 

AI vs. Generative AI: A Concise Overview (Anthropic, 2025)

Figure 1. An AI generated image of generative AI
Anthropomorphic image of generative AI

Note. Image created using Midjourney. The image was generated in response to the prompt: an anthropomorphic representation of generative AI

 

Artificial Intelligence (AI) refers to systems that perform tasks requiring human intelligence. Traditional AI excels at:

  • Analyzing existing data
  • Recognizing patterns
  • Making predictions
  • Optimizing processes
  • Classification tasks

Examples: Medical diagnostic systems, fraud detection algorithms, recommendation engines, and industrial quality control systems.


Generative AI is a subset of AI that creates new content rather than just analyzing existing data. It can produce:

  • Original text (essays, stories, code)
  • Images and artwork
  • Music compositions
  • Video content

Examples: Large Language Models like [Claude], image generators like DALL-E, music composition AI, and code generation tools.

The fundamental difference: Traditional AI provides answers or decisions from existing possibilities, while Generative AI creates entirely new content that didn't previously exist. Traditional AI might identify a cat in an image; Generative AI can create a new image of a cat based on your description.

 

References (APA):

Anthropic Claude 3.5 Sonnet  (2025) Claude.ai response to Sandra Dunkin 26 February. 

Midjourney Inc. (2025) Midjourney (6.1) [AI image generator] https://cdn.midjourney.com